Due to the ever increasing dependence on wireless communication in both civilian and military environments, the blocking of wireless communication, i.e., jamming, is one of the major security threats that must be addressed. Several jammer categories have been identified, according to their channel-awareness and “statefulness.” Traditionally, constant and random jammers have been the prevalent approaches to jamming, because they are easy to implement. However, these methods lack channel-awareness, and are generally inefficient in blocking communications, especially when the “signals of interest” (SOI's) utilize sophisticated protocols such as “channel-hopping.” In addition, constant or random jamming is relatively easy to detect, and therefore disadvantageous for hostile entities that may wish to elude detection and apprehension.
On the other end of the spectrum, reactive jammers which target only packets that are already “on the air,” base their jamming decisions on both the current and previous channel states of the SOI. This allows for effective and efficient jamming, because only short jamming bursts are required to interfere with packets. In particular, reactive jamming enables the implementation of optimal jamming strategies, since channel-awareness is a major factor for such strategies. For example, it has been shown that a reactive jammer can be four orders of magnitude more efficient than a pre-emptive jammer. Furthermore, by corrupting the reception of only selected packets, only limited interference with other nodes is experienced, thereby minimizing the risk of detection.
Detection and characterization of reactive jamming requires that received signals must be analyzed to determine if they include significant interactions and correlations with the SOI. Currently, such estimations of interactions between communications systems and a periodic jammer that is recording and replaying receptions of the communication system are calculated using blind estimation. This current method is inaccurate and produces too many errors.
What is needed, therefore, are improved techniques for reliable detection and characterization of reactive jamming attacks.